Create ai tracking prompt

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (write, non-destructive, closed-world), the description discloses that revisions are immutable, that explicit budget consent is involved, and that no automatic paid baseline is started. These are real behavioral traits not present in the structured fields. Some phrases ('budget consent,' 'stable retry keys') are cryptic and map to no schema field, which weakens the clarity but does not negate the added context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with no padding, which is good. However, it front-loads the vaguest sentence ('Manage project-scoped AI tracking') and the middle sentence is a cryptic list that does not clearly connect to creating a prompt. Efficient but not well-structured around the actual action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a create mutation with eight parameters, nested provenance objects, and no output schema. The description covers the immutability/cost angle but says nothing about what is created or how the generation_reference / provider_dataset_reference provenance objects are expected to be supplied. The rich schema (88% coverage) and annotations carry most of the weight, leaving this just adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 88%, so the schema already documents nearly all eight parameters (text, label, paused, category, topic_id, project_id, and the two nested provenance objects). The description adds no parameter-level meaning, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The tool name signals creation, but the description opens with the generic verb 'Manage project-scoped AI tracking,' which does not actually state that a prompt is created. It never distinguishes this tool from its obvious siblings update_ai_tracking_prompt, archive_ai_tracking_prompt, or list_ai_tracking_prompts. An agent can infer the purpose from the name but the description itself is vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance and no named alternative (e.g., update vs create vs archive). The only usage-relevant statement is the negative scope note 'This does not start an automatic paid baseline,' which clarifies cost behavior but not tool selection. This is essentially no guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.